Implementation of Trading Strategies for Backtesting in MetaTrader 5 (MT5) Using MQL5 Programming Language – Free Open-Source Trading Bots (Expert Advisors) for MT5

QuantLib implementation in ImGui

A simple trading platform with separate server and client components

Demonstrates applied data science techniques (Jupyter Notebook) for financial or risk reporting, including visualization and statistical inference.

Fetches market data from the Alpha Vantage API, calculates daily returns for a portfolio of stocks, and computes the Value at Risk (VaR) at a 95% confidence level.

A backtesting and performance analysis package

Looks like nautilus trader is best for live trading, and bt is good for visualizing

Project 1 of the 2020 Northwestern Financial Technology Bootcamp. We built a functional quantitative trading system that implements strategies researched and tested in Quantopian. Those strategies are then executed in Alpaca- the commission-free stock trading API.